Nephrology

Prediction of mortality, bleeding, and ischaemic events in patients with cancer and acute coronary syndrome: a model development and validation study.

BACKGROUND: Accurate assessment of mortality, bleeding, and atherothrombotic risk in patients with cancer and acute coronary syndrome could inform novel personalised treatment strategies, but no standardised tools for this purpose exist. We aimed to develop and validate a clinically applicable risk score for mortality, bleeding, and ischaemic events in patients with cancer and acute coronary syndr...

How do dialysis nurses and AI reason clinically? A scenario-based comparative study.

Monocyte-to-HDL ratio (MHR) is associated with overall and renal mortality in community-dwelling older individuals with chronic kidney disease (CKD).

Early Implications for Solid Organ Transplantation With the Use of Artificial Intelligence From a Bibliometric Perspective.

Artificial intelligence (AI) is increasingly transforming health care, particularly in solid organ transplantation, where it addresses complex challen...

Machine Learning Predictions for Assessing Hard-to-Place Deceased Donor Kidneys.

RATIONALE & OBJECTIVE: Nearly 20% of deceased donor kidneys in the United States are placed "out-of-sequence" (ie, outside of standard allocation rule...

Development and validation of an interpretable machine learning model for early prediction of deterioration in patients with severe fever with thrombocytopenia syndrome.

BACKGROUND: Severe Fever with Thrombocytopenia Syndrome (SFTS) is a severe tick-borne viral infection with high mortality, making the timely predictio...

Characterizing the Immune Cell Infiltration in Renal Interstitium and Therapeutic Targets of Drugs in Diabetic Nephropathy by Multiomics Study.

BACKGROUND: Immune cell infiltration in the renal interstitium contributes to the progression of diabetic nephropathy (DN), yet the precise mechanisms...

Integrated artificial intelligence and omics for prediction and monitoring of pre-eclampsia.

Pre-eclampsia is a difficult pregnancy condition that causes high blood pressure and can lead to health complications in both mother and newborn, resu...

Artificial intelligence versus classical scoring systems: a comparative analysis of stone-free prediction after percutaneous nephrolithotomy.

This study aimed to compare the predictive performance of traditional stone scoring systems with a large language model based on ChatGPT in estimating...

Microvascular inflammation in the kidney transplant, beyond acute antibody-mediated rejection.

PURPOSE OF REVIEW: Microvascular inflammation (MVI) is a central feature of allograft rejection, traditionally associated with antibody-mediated rejec...

Frailty trajectories and risk of incident advanced CKM syndrome: A national cohort analysis.

BACKGROUND: The interplay between frailty dynamics and the newly defined Cardiovascular-Kidney-Metabolic (CKM) syndrome remains poorly understood. We ...

Ultrasound-Based Kidney Stone Classification Using Kronecker Self-Organizing Map Forward Harmonic Network.

Kidney stone disease is a prevalent urological disorder that can result in severe pain, obstruction, and long-term complications if not detected and m...

Network toxicology and experimental validation reveal TDCPP as an emerging environmental risk factor for chronic kidney disease.

BACKGROUND: Tris(1,3-dichloro-2-propyl) phosphate (TDCPP) is a widely used organophosphorus flame retardant that has raised growing concern because it...

Unraveling heterogeneity in LUAD via multi-omics integration: molecular classification and therapeutic implications.

Lung adenocarcinoma (LUAD) displays significant morphological and molecular heterogeneity both within and between tumors. This heterogeneity, coupled ...

Forecasting Waitlist Trajectories for Patients With Metabolic Dysfunction-Associated Steatohepatitis Cirrhosis: A Neural Network Competing Risk Analysis.

BACKGROUND: Metabolic dysfunction-associated steatohepatitis (MASH) cirrhosis is a leading indication for liver transplantation (LT). Patients with MA...

Improving Robustness and Training Efficiency of Machine-Learned Potentials by Incorporating Short-Range Empirical Potentials.

Machine learning force fields (MLFFs) are powerful tools for materials modeling, but their performance is often limited by training data set quality, ...

Radiomics-based gradient boosting model on contrast-enhanced MRI for non-invasive prediction of epidermal growth factor receptor expression and therapeutic response to EGFR-targeted antibody-drug conjugates in high-grade glioma organoid models.

BACKGROUND: Epidermal growth factor (EGF) and its receptor EGF(EGFR) play crucial roles in glioblastoma (GBM) prognosis. However, non-invasive assessm...

Optimizing Early Detection of Diabetic Kidney Disease through Synergistic Biomarkers and Serum Metabolites in Human.

BACKGROUND: Diabetic kidney disease (DKD) progresses to end-stage renal disease more rapidly than chronic kidney disease due to persistent hyperglycem...

Digital hypertension in 2024-2025: emerging evidence and future directions.

Recent advances in digital technology are remarkable, and they are driving profound transformations in healthcare and medical research. Within this co...

Glomeruli detection and classification in histopathological images using deep learning semantic segmentation.